StaTDS library: Statistical tests for Data Science
In Data Science, there is a continual demand for statistical comparison to identify the most advantageous algorithms. Finding a software tool that facilitates the execution of multiple tests on different Data Science experiments without relying on additional libraries poses a challenge. This paper i...
Saved in:
| Published in | Neurocomputing (Amsterdam) Vol. 595; p. 127877 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
28.08.2024
|
| Subjects | |
| Online Access | Get full text |
| ISSN | 0925-2312 1872-8286 1872-8286 |
| DOI | 10.1016/j.neucom.2024.127877 |
Cover
| Abstract | In Data Science, there is a continual demand for statistical comparison to identify the most advantageous algorithms. Finding a software tool that facilitates the execution of multiple tests on different Data Science experiments without relying on additional libraries poses a challenge. This paper introduces StaTDS, an open-source library and web application implemented entirely in pure Python, designed to analyze, test, and compare Data Science algorithms. StaTDS implements all statistical tests without external dependencies. It ensures its durability and avoids future uncontrolled deprecated dependencies. With support for a wide variety of statistical tests (24 in total), StaTDS surpasses existing libraries dedicated to statistical testing. Moreover, the library incorporates tests to guide users in determining whether to employ parametric or non-parametric tests, such as the assessment of normality and homoscedasticity. This platform-independent library is available on GitHub under the GNU General Public License. |
|---|---|
| AbstractList | In Data Science, there is a continual demand for statistical comparison to identify the most advantageous algorithms. Finding a software tool that facilitates the execution of multiple tests on different Data Science experiments without relying on additional libraries poses a challenge. This paper introduces StaTDS, an open-source library and web application implemented entirely in pure Python, designed to analyze, test, and compare Data Science algorithms. StaTDS implements all statistical tests without external dependencies. It ensures its durability and avoids future uncontrolled deprecated dependencies. With support for a wide variety of statistical tests (24 in total), StaTDS surpasses existing libraries dedicated to statistical testing. Moreover, the library incorporates tests to guide users in determining whether to employ parametric or non-parametric tests, such as the assessment of normality and homoscedasticity. This platform-independent library is available on GitHub under the GNU General Public License. |
| ArticleNumber | 127877 |
| Author | Luna, Christian Moya, Antonio R. Luna, José María Ventura, Sebastián |
| Author_xml | – sequence: 1 givenname: Christian orcidid: 0009-0005-7502-0254 surname: Luna fullname: Luna, Christian email: i82luesc@uco.es – sequence: 2 givenname: Antonio R. orcidid: 0000-0002-3657-4749 surname: Moya fullname: Moya, Antonio R. email: amoya@uco.es – sequence: 3 givenname: José María orcidid: 0000-0003-3537-2931 surname: Luna fullname: Luna, José María email: jmluna@uco.es – sequence: 4 givenname: Sebastián orcidid: 0000-0003-4216-6378 surname: Ventura fullname: Ventura, Sebastián email: sventura@uco.es |
| BookMark | eNqNkMtOwzAQRS1UJNrCH7DIDyTY4zycLpBQy0uqxCJlbU39kFylSWW7oP49qcKKBbAazeLcmXNnZNL1nSHkltGMUVbe7bLOHFW_z4BCnjGoRFVdkCkTFaQCRDkhU1pDkQJncEVmIewoZRWDekqgibhZNUnrth79aZEMe3QhOoVtEk2IIbG9T1YYMWmUM50y1-TSYhvMzfeck_enx83yJV2_Pb8uH9ap4gXE1Ioty9k2R06ZrpnOAa2AnAu0trJ1ySpltB2eBQ28UJobpYtSKKpMWSIaPifFmHvsDnj6xLaVB-_2w5eSUXkWlzs5isuzuBzFB24xcsr3IXhjpXJnqb6LHl37F5z_gP95837EzFDIhzNehrEs7bxRUere_R7wBZKvic4 |
| CitedBy_id | crossref_primary_10_1016_j_eswa_2024_125955 crossref_primary_10_1016_j_ins_2024_120981 crossref_primary_10_1016_j_knosys_2024_112897 crossref_primary_10_1016_j_engappai_2025_110656 |
| Cites_doi | 10.1093/biomet/52.3-4.591 10.1093/biomet/58.2.341 10.1038/s41592-019-0686-2 10.1080/01621459.1986.10478341 10.1080/03610928008827904 10.1016/j.ins.2009.12.010 |
| ContentType | Journal Article |
| Copyright | 2024 The Author(s) |
| Copyright_xml | – notice: 2024 The Author(s) |
| DBID | 6I. AAFTH AAYXX CITATION ADTOC UNPAY |
| DOI | 10.1016/j.neucom.2024.127877 |
| DatabaseName | ScienceDirect Open Access Titles Elsevier:ScienceDirect:Open Access CrossRef Unpaywall for CDI: Periodical Content Unpaywall |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: UNPAY name: Unpaywall url: https://proxy.k.utb.cz/login?url=https://unpaywall.org/ sourceTypes: Open Access Repository |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISSN | 1872-8286 |
| ExternalDocumentID | 10.1016/j.neucom.2024.127877 10_1016_j_neucom_2024_127877 S0925231224006489 |
| GroupedDBID | --- --K --M .DC .~1 0R~ 123 1B1 1~. 1~5 4.4 457 4G. 53G 5VS 6I. 7-5 71M 8P~ 9JM 9JN AABNK AACTN AAEDT AAEDW AAFTH AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAXLA AAXUO AAYFN ABBOA ABCQJ ABFNM ABJNI ABMAC ACDAQ ACGFS ACRLP ACZNC ADBBV ADEZE AEBSH AEKER AENEX AFKWA AFTJW AFXIZ AGHFR AGUBO AGWIK AGYEJ AHHHB AHZHX AIALX AIEXJ AIKHN AITUG AJOXV AKRWK ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD AXJTR BKOJK BLXMC CS3 DU5 EBS EFJIC EO8 EO9 EP2 EP3 F5P FDB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ IHE J1W KOM LG9 M41 MO0 MOBAO N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 RIG ROL RPZ SDF SDG SDP SES SEW SPC SPCBC SSN SSV SSZ T5K ZMT ~G- 29N AAQXK AATTM AAXKI AAYWO AAYXX ABWVN ABXDB ACLOT ACNNM ACRPL ACVFH ADCNI ADJOM ADMUD ADNMO AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKYEP ANKPU APXCP ASPBG AVWKF AZFZN CITATION EFKBS EFLBG EJD FEDTE FGOYB HLZ HVGLF HZ~ R2- SBC WUQ XPP ~HD ADTOC AGCQF UNPAY |
| ID | FETCH-LOGICAL-c352t-f8b141b4a301d91d42af82438aff7f9617cedf1272d235cd3ecd568c0ce66aae3 |
| IEDL.DBID | .~1 |
| ISSN | 0925-2312 1872-8286 |
| IngestDate | Tue Aug 19 21:09:46 EDT 2025 Wed Oct 01 05:03:38 EDT 2025 Thu Apr 24 23:04:24 EDT 2025 Tue Jun 18 08:52:15 EDT 2024 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Statistical tests Data science comparison Python |
| Language | English |
| License | This is an open access article under the CC BY-NC-ND license. cc-by-nc-nd |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c352t-f8b141b4a301d91d42af82438aff7f9617cedf1272d235cd3ecd568c0ce66aae3 |
| ORCID | 0000-0003-4216-6378 0009-0005-7502-0254 0000-0003-3537-2931 0000-0002-3657-4749 |
| OpenAccessLink | https://www.sciencedirect.com/science/article/pii/S0925231224006489 |
| ParticipantIDs | unpaywall_primary_10_1016_j_neucom_2024_127877 crossref_citationtrail_10_1016_j_neucom_2024_127877 crossref_primary_10_1016_j_neucom_2024_127877 elsevier_sciencedirect_doi_10_1016_j_neucom_2024_127877 |
| ProviderPackageCode | CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2024-08-28 |
| PublicationDateYYYYMMDD | 2024-08-28 |
| PublicationDate_xml | – month: 08 year: 2024 text: 2024-08-28 day: 28 |
| PublicationDecade | 2020 |
| PublicationTitle | Neurocomputing (Amsterdam) |
| PublicationYear | 2024 |
| Publisher | Elsevier B.V |
| Publisher_xml | – name: Elsevier B.V |
| References | Rodríguez-Fdez, Canosa, Mucientes, Bugarín (b3) 2015 Snedecor, Cochran (b8) 1989 Virtanen, Gommers, Oliphant, Haberland, Reddy, Cournapeau, Burovski, Peterson, Weckesser, Bright, van der Walt, Brett, Wilson, Millman, Mayorov, Nelson, Jones, Kern, Larson, Carey, Polat, Feng, Moore, VanderPlas, Laxalde, Perktold, Cimrman, Henriksen, Quintero, Harris, Archibald, Ribeiro, Pedregosa, van Mulbregt, SciPy 1.0 Contributors (b2) 2020; 17 García, Fernández, Luengo, Herrera (b1) 2010; 180 (b6) 2023 Demšar (b10) 2006; 7 Levene (b7) 1960; vol. 278 Shaffer (b12) 1986; 81 Ss (b4) 1965; 52 Iman, Davenport (b11) 1980; 9 d’Agostino (b5) 1971; 58 Sheskin (b9) 2020 Ss (10.1016/j.neucom.2024.127877_b4) 1965; 52 Levene (10.1016/j.neucom.2024.127877_b7) 1960; vol. 278 Sheskin (10.1016/j.neucom.2024.127877_b9) 2020 García (10.1016/j.neucom.2024.127877_b1) 2010; 180 Rodríguez-Fdez (10.1016/j.neucom.2024.127877_b3) 2015 d’Agostino (10.1016/j.neucom.2024.127877_b5) 1971; 58 Snedecor (10.1016/j.neucom.2024.127877_b8) 1989 Demšar (10.1016/j.neucom.2024.127877_b10) 2006; 7 Virtanen (10.1016/j.neucom.2024.127877_b2) 2020; 17 Shaffer (10.1016/j.neucom.2024.127877_b12) 1986; 81 (10.1016/j.neucom.2024.127877_b6) 2023 Iman (10.1016/j.neucom.2024.127877_b11) 1980; 9 |
| References_xml | – volume: 52 start-page: 591 year: 1965 end-page: 611 ident: b4 article-title: An analysis of variance test for normality (complete samples) publication-title: Biometrika – year: 1989 ident: b8 publication-title: Statistical Methods – volume: vol. 278 start-page: 292 year: 1960 ident: b7 article-title: Contributions to probability and statistics publication-title: Essays in Honor of Harold Hotelling – start-page: 1 year: 2015 end-page: 8 ident: b3 article-title: STAC: a web platform for the comparison of algorithms using statistical tests publication-title: 2015 IEEE International Conference on Fuzzy Systems – volume: 180 start-page: 2044 year: 2010 end-page: 2064 ident: b1 article-title: Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power publication-title: Inf. Sci. – year: 2020 ident: b9 article-title: Handbook of Parametric and Nonparametric Statistical Procedures – volume: 9 start-page: 571 year: 1980 end-page: 595 ident: b11 article-title: Approximations of the critical region of the fbietkan statistic publication-title: Comm. Statist. Theory Methods – volume: 7 start-page: 1 year: 2006 end-page: 30 ident: b10 article-title: Statistical comparisons of classifiers over multiple data sets publication-title: J. Mach. Learn. Res. – volume: 81 start-page: 826 year: 1986 end-page: 831 ident: b12 article-title: Modified sequentially rejective multiple test procedures publication-title: J. Amer. Statist. Assoc. – volume: 58 start-page: 341 year: 1971 end-page: 348 ident: b5 article-title: An omnibus test of normality for moderate and large size samples publication-title: Biometrika – volume: 17 start-page: 261 year: 2020 end-page: 272 ident: b2 article-title: SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python publication-title: Nature Methods – year: 2023 ident: b6 article-title: NIST/SEMATECH e-Handbook of Statistical Methods – volume: 52 start-page: 591 year: 1965 ident: 10.1016/j.neucom.2024.127877_b4 article-title: An analysis of variance test for normality (complete samples) publication-title: Biometrika doi: 10.1093/biomet/52.3-4.591 – year: 2023 ident: 10.1016/j.neucom.2024.127877_b6 – year: 2020 ident: 10.1016/j.neucom.2024.127877_b9 – start-page: 1 year: 2015 ident: 10.1016/j.neucom.2024.127877_b3 article-title: STAC: a web platform for the comparison of algorithms using statistical tests – year: 1989 ident: 10.1016/j.neucom.2024.127877_b8 – volume: 58 start-page: 341 issue: 2 year: 1971 ident: 10.1016/j.neucom.2024.127877_b5 article-title: An omnibus test of normality for moderate and large size samples publication-title: Biometrika doi: 10.1093/biomet/58.2.341 – volume: 17 start-page: 261 year: 2020 ident: 10.1016/j.neucom.2024.127877_b2 article-title: SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python publication-title: Nature Methods doi: 10.1038/s41592-019-0686-2 – volume: 81 start-page: 826 issue: 395 year: 1986 ident: 10.1016/j.neucom.2024.127877_b12 article-title: Modified sequentially rejective multiple test procedures publication-title: J. Amer. Statist. Assoc. doi: 10.1080/01621459.1986.10478341 – volume: 9 start-page: 571 issue: 6 year: 1980 ident: 10.1016/j.neucom.2024.127877_b11 article-title: Approximations of the critical region of the fbietkan statistic publication-title: Comm. Statist. Theory Methods doi: 10.1080/03610928008827904 – volume: vol. 278 start-page: 292 year: 1960 ident: 10.1016/j.neucom.2024.127877_b7 article-title: Contributions to probability and statistics – volume: 7 start-page: 1 year: 2006 ident: 10.1016/j.neucom.2024.127877_b10 article-title: Statistical comparisons of classifiers over multiple data sets publication-title: J. Mach. Learn. Res. – volume: 180 start-page: 2044 issue: 10 year: 2010 ident: 10.1016/j.neucom.2024.127877_b1 article-title: Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power publication-title: Inf. Sci. doi: 10.1016/j.ins.2009.12.010 |
| SSID | ssj0017129 |
| Score | 2.4756174 |
| Snippet | In Data Science, there is a continual demand for statistical comparison to identify the most advantageous algorithms. Finding a software tool that facilitates... |
| SourceID | unpaywall crossref elsevier |
| SourceType | Open Access Repository Enrichment Source Index Database Publisher |
| StartPage | 127877 |
| SubjectTerms | Data science comparison Python Statistical tests |
| SummonAdditionalLinks | – databaseName: Unpaywall dbid: UNPAY link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlZ3PS8MwFMcfczvoxfkT5y968GjKmqZp6204xxA2BDeYp5KfBx11aIvoX2_SH0OFsXks5LXpey_k0-blG4ArX2jlU6kQ8UKKSBR0USQpRphQhTXBXBaiPqMxHU7J_SyYNeC63gvza_2-qMNKVW7rOsxHOnE9bPIr3IIWDQx5N6E1HT_0ngo5PRwggyrF4mYU4mJ3dL1TbsVtVs1E23m6YJ8fbD7_MdMM2jCq-1gWmLy4ecZd8fVHvnHTl9iD3Qo5nV6ZI_vQUOkBtOvjHJxqdB8CNuA56T861Y-dG8eCaKHjbKwNkWbvjiFcp88yVhsdwXRwN7kdoupIBSQMaWVIR9wjHifMjGsZe5JgpiNM_IhpHerY4IxQUpseYon9QEhfCRnQSHSFopQx5R9DM31N1Qk4MWWiy7o8JlYvJg65bcBNfLUwaeEFHfBr9yai0hu3x17Mk7qw7Dkp3ZJYtySlWzqAllaLUm9jTfuwjlxSMUPJAokJwhpLdxnojR51-l-DM9ixV_YPNI7OoZm95erCIEzGL6vM_QbZB-n9 priority: 102 providerName: Unpaywall |
| Title | StaTDS library: Statistical tests for Data Science |
| URI | https://dx.doi.org/10.1016/j.neucom.2024.127877 https://doi.org/10.1016/j.neucom.2024.127877 |
| UnpaywallVersion | publishedVersion |
| Volume | 595 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Baden-Württemberg Complete Freedom Collection (Elsevier) customDbUrl: eissn: 1872-8286 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0017129 issn: 0925-2312 databaseCode: GBLVA dateStart: 20110101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVESC databaseName: Elsevier E-journals (Freedom Collection) customDbUrl: eissn: 1872-8286 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0017129 issn: 0925-2312 databaseCode: ACRLP dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVESC databaseName: Elsevier ScienceDirect customDbUrl: eissn: 1872-8286 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0017129 issn: 0925-2312 databaseCode: .~1 dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals [SCFCJ] customDbUrl: eissn: 1872-8286 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0017129 issn: 0925-2312 databaseCode: AIKHN dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier – providerCode: PRVLSH databaseName: Elsevier Journals customDbUrl: mediaType: online eissn: 1872-8286 dateEnd: 99991231 omitProxy: true ssIdentifier: ssj0017129 issn: 0925-2312 databaseCode: AKRWK dateStart: 19930201 isFulltext: true providerName: Library Specific Holdings |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3NS8MwFA9jHvTitzg_Rg9eszVpmqbexqZMxSHMwTyVNE1gMurQDvHi3-5Lmw49yMRTaXmPtL-XvPwa3gdCF4EyOuCZxoxEHDMR-lhknGLKuKaG0TQri_rcj_hwwm6n4bSB-nUujA2rdL6_8umlt3ZPug7N7mI26479mMJfFCmjIDkTNomPsch2Meh8rsI8SERoVW-PhthK1-lzZYxXrpc2ZoTCRtUhFOZu9Nv2tLnMF_LjXc7n37af61207Xij16tebQ81dL6PduqeDJ5bogeIAnt8HIw9dzpz6Vk2WRZjBm2glcWbBzTVG8hC1kqHaHJ99dgfYtcXASugSwU2IiWMpEzC4sxikjEqjaAsENKYyMTASQA8A99DMxqEKgu0ykIulK8051Lq4Ag185dcHyMv5lL50k9jZou-xFFqBVIwklFgWxK2UFDDkShXNNz2rpgndXTYc1KBmFgQkwrEFsIrrUVVNGONfFQjnfwwfgJ-fY1mZ2WYPw118u-hTtGWvbPnyVScoWbxutTnQEiKtF3OuDba6N3cDUdwnYweek9f9KvgaA |
| linkProvider | Elsevier |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV07T8MwELZKGcrCG1GeGVjdxo7jOGyopSrQdmkrdbMcx5aKqlBBKsTCb8dOnAoGVMSa3MnJd_bdZ-t8B8BNILUKaKogQRGFhIU-ZCnFEBOqsCY4SYuiPsMR7U_J4yyc1UCnugtj0yqd7y99euGt3ZO2Q7O9nM_bYz_GZheFiixISli8BbZJiCO7A2t9rvM8UIRwWXAPh9CKV_fniiSvTK1s0gg2kaqFsJm80W_xqbHKluLjXSwW3-JPbx_sOuLo3ZXfdgBqKjsEe1VTBs-t0SOADX2cdMeeO5659SydLKoxG23DK_M3z_BUrytyUSkdg2nvftLpQ9cYAUrDl3KoWYIISogwqzONUUqw0AyTgAmtIx0bUmLQ0-Z_cIqDUKaBkmlImfSlolQIFZyAevaSqVPgxVRIX_hJTGzVlzhKrEBirKSlMS4KmyCo4ODSVQ23zSsWvEoPe-YliNyCyEsQmwCutZZl1YwN8lGFNP9hfW4c-wbN1towfxrq7N9DXYNGfzIc8MHD6Okc7Ng39nAZswtQz19X6tKwkzy5KmbfFzwX4E0 |
| linkToUnpaywall | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlZ3PS8MwFMcfczvoxfkT5y968GjKmqZp6204xxA2BDeYp5KfBx11aIvoX2_SH0OFsXks5LXpey_k0-blG4ArX2jlU6kQ8UKKSBR0USQpRphQhTXBXBaiPqMxHU7J_SyYNeC63gvza_2-qMNKVW7rOsxHOnE9bPIr3IIWDQx5N6E1HT_0ngo5PRwggyrF4mYU4mJ3dL1TbsVtVs1E23m6YJ8fbD7_MdMM2jCq-1gWmLy4ecZd8fVHvnHTl9iD3Qo5nV6ZI_vQUOkBtOvjHJxqdB8CNuA56T861Y-dG8eCaKHjbKwNkWbvjiFcp88yVhsdwXRwN7kdoupIBSQMaWVIR9wjHifMjGsZe5JgpiNM_IhpHerY4IxQUpseYon9QEhfCRnQSHSFopQx5R9DM31N1Qk4MWWiy7o8JlYvJg65bcBNfLUwaeEFHfBr9yai0hu3x17Mk7qw7Dkp3ZJYtySlWzqAllaLUm9jTfuwjlxSMUPJAokJwhpLdxnojR51-l-DM9ixV_YPNI7OoZm95erCIEzGL6vM_QbZB-n9 |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=StaTDS+library%3A+Statistical+tests+for+Data+Science&rft.jtitle=Neurocomputing+%28Amsterdam%29&rft.au=Luna%2C+Christian&rft.au=Moya%2C+Antonio+R.&rft.au=Luna%2C+Jos%C3%A9+Mar%C3%ADa&rft.au=Ventura%2C+Sebasti%C3%A1n&rft.date=2024-08-28&rft.issn=0925-2312&rft.volume=595&rft.spage=127877&rft_id=info:doi/10.1016%2Fj.neucom.2024.127877&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_neucom_2024_127877 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0925-2312&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0925-2312&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0925-2312&client=summon |